Shadows are formed whenever an occlusion partially blocks the illumination of a surface or object by a light source. With the exception of the ambient light, which is assumed to be omni-directional, light sources illuminate surfaces from only one specific direction. In addition to classification by the source direction, shadows are further classified into “self” and “cast”. A “self” shadow refers to the regions of an object not directly illuminated by a light source due to its surface orientation, whereas a “cast” shadow refers to a region not illuminated by a source due to occlusion by other objects. Shadowed regions usually appear darker than the lit regions and their color properties (e.g., hue and saturation) can also appear different than the directly illuminated regions. Such differences in intensity and color create patterns and boundaries/edges that often confuse human observers or machine vision algorithms that attempt to segment scenes and identify objects using these cues. For this reason, many techniques have been developed to identify, segment, and remove shadows from an image or a video sequence. However, all previously published methods use only two aspects of light—its intensity and/or spectral (“color”) distribution—as information in shadow segmentation. However, in some cases these are combined with available temporal and geometric information. It appears that a third fundamental property of light—its polarization—has not heretofore been used for the purpose of shadow segmentation. Furthermore, most existing shadow segmentation algorithms assume a relatively simple shadow model: an area of a scene is classified either as shadow or non-shadow. In fact, it is possible for a specific region of a scene to be both shadow for one source and illuminated simultaneously by another source or sources, as explained below. In such cases, polarization information can assist in “parsing” such complications in scene segmentation.
Polarization is an intrinsic property of light. Light from the dominant natural source, the sun, is not polarized, but light scattered from small particles in the sky and most light reflected or scattered from object surfaces is partially polarized. The unaided human eye and most machine vision cameras are “blind” to polarization, but some animal species can detect and utilize polarization information and use it for a variety of purposes, including navigation and object recognition. Inspired by biological polarization vision, the present inventors have previously developed polarization sensitive cameras and processing methods for the detection of targets in scattering media, detecting latent fingerprints and enhancing surveillance. (See M. P. Rowe, E. N. Jr. Pugh, and N. Engheta, “Polarization-difference imaging: a biologically inspired technique for observation through scattering media,” Opt. Lett. 20, 608-610 (1995); J. S. Tyo, M. P. Rowe, E. N. Jr. Pugh, and N. Engheta, “Target detection in optically scatter media by polarization-difference imaging,” Appl. Opt. 35, 1855-1870 (1996); S.-S. Lin, K. M. Yemelyanov, E. N. Jr. Pugh, and N. Engheta, “Polarization Enhanced Visual Surveillance Techniques,” in Proc. of IEEE Int. Conf. on Networking, Sensing and Control (IEEE Syst. Man. Cybern. Society, Taipei, Taiwan, 2004). The inventors have also previously developed methods for displaying polarization information effectively to human observers. (See J. S. Tyo, E. N. Jr. Pugh, and N. Engheta, “Colorimetric representation for use with polarization-difference imaging of objects in scattering media,” J. Opt. Soc. Am. A 15, 367-374 (1998); K. M. Yemelyanov, M. A. Lo, E. N. Jr. Pugh, and N. Engheta, “Display of polarization information by coherently moving dots,” Opt. Express 11, 1577-1584 (2003).) It has been reported that polarization increases in dark surface area (W. G. Egan, “Dark-target retroreflection increase,” in Proc. SPIE, Polarization: Measurement, Analysis, and Remote Sensing 11 (SPIE1999), 3754, pp. 218-225), and that polarization can be used to enhance details in shadow (M. J. Duggin, “Imaging polarimetry in scene element discrimination,” in Proc. SPIE, Polarization: Measurement, Analysis, and Remote Sensing II (SPIE1999), 3754, pp. 108-117). It has also been reported that polarization increases with increasing incident light angle (D. H. Goldstein, D. B. Chenault, and J. L. Pezzaniti, “Polarimetric characterization of Spectralon,” in Proc. SPIE, Polarization: Measurement, Analysis, and Remote Sensing II (SPIE1999), 3754, pp. 126-136).
However, complex overlapping cast shadows remain almost impossible to distinguish in images generated with only intensity and color information. A technique is desired that allows such complex overlapping cast shadows to be readily segmented from each other in images generated from the polarization parameters of a scene. The present invention addresses this need in the art.